How Artificial Intelligence Is Reshaping Orthodontics: A Global Research Overview
A bibliometric look at where AI in orthodontics stands today—and where it’s heading next
Artificial intelligence (AI) is no longer a futuristic concept in healthcare. In orthodontics, AI has rapidly moved from experimental ideas to practical tools that support diagnosis, treatment planning, and clinical efficiency. A new study published in Clinical Oral Investigations (2025) takes a step back to examine this fast-growing field from a broader perspective—by analyzing global research trends rather than individual technologies.
Instead of testing one AI system, the researchers asked a bigger question: How is AI research in orthodontics evolving worldwide, and what does it tell us about the future of clinical practice?
Why This Study Matters
Over the last decade, orthodontics has undergone a major digital transformation. Manual workflows have gradually been replaced by digital imaging, computerized analysis, and automated tools. AI sits at the center of this transformation, promising faster diagnoses, greater consistency, and more personalized care.
However, with hundreds of AI-related studies published in recent years, it has become increasingly difficult to see the “big picture.” This study helps clarify that landscape by identifying:
Which AI applications dominate orthodontic research
Which countries and institutions lead innovation
Which research areas are growing—and which remain underexplored
What the Researchers Did
The authors conducted a bibliometric analysis, a quantitative method used to map scientific literature. Using the Web of Science Core Collection, they analyzed 381 original research articles published between 1991 and mid-2024 that focused on AI applications in orthodontics.
Specialized software (CiteSpace and VOSviewer) was used to examine:
Publication trends over time
Influential journals and articles
Leading authors, institutions, and countries
Research “hotspots” identified through keyword analysis
This approach allowed the team to visualize how AI research in orthodontics has grown and where it is most concentrated.
A Rapid Surge in AI Research
One of the clearest findings is just how recent and fast-moving this field is.
Nearly 83% of all analyzed studies were published in the last three and a half years (2021–2024). The year 2023 alone marked the peak of publications, highlighting a surge of scientific interest.
This explosive growth reflects both technological advances in machine learning and the increasing availability of digital orthodontic data, such as CBCT scans and digital radiographs.
Who Is Leading AI Research in Orthodontics?
Countries and Institutions
Research output is heavily concentrated in a few regions:
China, the United States, and South Korea together account for about two-thirds of all publications.
Leading institutions include Seoul National University, Yonsei University, Sichuan University, and Peking University.
These patterns likely reflect differences in research funding, infrastructure, and national investment in AI-driven healthcare.
Journals and Disciplines
While many studies appear in top orthodontic journals—such as the American Journal of Orthodontics and Dentofacial Orthopedics and The Angle Orthodontist—a significant number are published in computer science and medical imaging journals.
This highlights the strongly multidisciplinary nature of AI research, where orthodontists collaborate with engineers and data scientists.
What Are the Main AI Applications Being Studied?
Keyword analysis revealed two dominant research themes:
1. Automated Cephalometric Analysis
AI systems are widely studied for identifying anatomical landmarks on 2D and 3D images. These tools aim to:
Reduce analysis time
Minimize human subjectivity
Improve consistency across clinicians
While accuracy has improved significantly, the study notes that AI systems do not yet consistently outperform experienced clinicians, especially when strict clinical accuracy thresholds are applied.
2. Automatic Image Segmentation
Another major focus is AI-driven segmentation of teeth, bones, and airways from CBCT images. Compared to manual segmentation—which is slow and operator-dependent—AI offers near-instant results.
However, challenges remain, particularly when image quality is poor or dental anatomy is complex (such as crowded teeth or overlapping structures).
Promising—but Still Emerging—Applications
Some areas show potential but remain underexplored:
AI-assisted treatment planning
Prediction of facial and soft-tissue changes
Decisions about tooth extraction
Growth and skeletal maturity assessment
Current evidence suggests encouraging accuracy, but the authors emphasize that most studies still lack strong clinical validation, large datasets, or standardized evaluation methods.
What This Means for Clinical Practice
Despite impressive progress, the study makes one point clear: AI in orthodontics is still in a developmental phase.
To move from research to routine clinical use, future studies must:
Use larger and more diverse datasets
Apply standardized reporting guidelines
Validate AI tools in real clinical settings
Collaboration across institutions and countries will be essential to build robust, trustworthy AI systems that clinicians can rely on.
Conclusion
This bibliometric analysis paints a clear picture of a rapidly expanding field driven by technological innovation and global collaboration. AI is already transforming how orthodontic data are analyzed, especially in imaging-based diagnostics.
However, while efficiency gains are evident, clinical reliability and generalizability remain the key challenges ahead. With continued research and careful validation, AI has the potential to become an integral—and trusted—partner in orthodontic care.
Original Article Reference
Polizzi, A., Boato, M., Serra, S., D’Antò, V., & Leonardi, R. (2025).
Applications of artificial intelligence in orthodontics: A bibliometric and visual analysis.
Clinical Oral Investigations, 29, Article 65.
DOI: https://doi.org/10.1007/s00784-025-06158-y